Generally, security systems employ an identity-based authentication scheme to verify the identity of an entity before granting access to a computer system or a computerized resource. One goal of such security systems is to accurately determine identity so that an unauthorized party cannot gain access. Security systems can use one or more of several factors, alone or in combination, to authenticate entities. For example, security systems can be based on something that the entity knows, something the entity is or something that the entity has.
Examples of something an entity knows are a code word, password, personal identification number (“PIN”) and the like. Examples of something the entity is include a distinct characteristic or attribute known as a biometric. An example of something an entity possesses is a physical or digital object, referred to generally as a token, that is unique, or relatively unique, to the user.
Computer-based event probability prediction systems traditionally use some amount of historical information, a profile, about individual objects in order to compare present behavior with past behavior. Each of these objects is defined to be an entity, while a set of similar objects is defined to be an entity class. Examples of events to predict include whether or not a loan applicant will default on a loan and whether or not a credit card transaction is fraudulent. Examples of entities include a particular customer account at a bank and a particular Automatic Teller Machine (ATM).
To achieve high performance, an event probability prediction system often includes a mathematical model or combination of models which extracts patterns from historical data and uses the patterns on the present transaction data to calculate a score, a number that represents the likelihood that a particular event will occur.